The present invention relates to a method and apparatus for processing images to detect particular features in the image. It is particularly concerned with the detection of features in noisy 2D, 2D+T, 3D and 3D+T images, and is thus particularly useful in medical imaging, for instance using ultrasound.
There are a variety of techniques for processing images to enhance them, particularly to reduce the amount of noise and/or to detect features of interest in the image. Such techniques are particularly useful in areas where images are noisy, for instance in medical imaging. For example, ultrasound images include a considerable amount of speckle which makes images difficult to interpret. Skilled operators are able to interpret such images based on their experience and knowledge of the features of interest likely to be present. However, automating the process of detecting features of interest is made difficult by the presence of noise and imaging artefacts. Similar problems arise in other imaging techniques, such as magnetic resonance imaging.
In general up to now techniques proposed for enhancing images have been based on examining the intensity of the image, for instance by smoothing the intensity to reduce noise or by setting a detection threshold based on amplitude. However, techniques based on thresholding are not entirely satisfactory because of the difficulty of setting a suitable global threshold. For instance, ultrasound images include attenuation artifacts caused by the changing orientation and reflectivity of the tissue being imaged. Choosing one threshold which is suitable for excluding noise, but including all features of interest, is difficult if not impossible.
Other techniques have been proposed for analysing noisy images for detecting features which are based on correlating images over time or with movement of the imaging probe. For instance, ultrasound speckle decorrelates with movement of the probe and over time. A problem with some of these techniques, however, is that they tend to blur the features of interest in the image. Thus the user has to accept to trade-off between removing noise and losing image quality.
It is therefore an object of the invention to provide a technique for automatic detection of features of interest in an image which improves on the prior art techniques.
The present invention provides a method for detecting features of interest in an image based on the shape of the intensity profile of the feature, rather than its intensity. This is achieved by an intensity independent comparison of the intensity profile across the image with a shape model of features of interest. To improve subsequent processing of the image, areas of the image which are detected as corresponding to the shape model are labelled with a description of their properties.
In more detail, therefore, the present invention provides a method of detecting features-of-interest in an image, comprising the steps of:                making an intensity independent comparison of the shape of regions of the intensity profile across the image with a shape model for predefined features of interest to define as features of interest areas of the image satisfying the shape model; and        storing for each of said defined areas a label comprising the level of similarity to the shape model.        
The predefined features of interest may be positive and negative step edges, or roof or ridge shapes, or valleys or other features as desired depending on the application.
The label may include a measure of the orientation of the feature in the image, and the comparison may also be performed on an intensity profile taken across successive frames of an image sequence to derive a measure of the velocity of image features. The label may then comprise a measure of the velocity.
The comparison with the shape model is advantageously performed in the spatial or spatio temporal frequency domains, thus by decomposing the intensity profile into spatial frequency components and examining the phase and amplitude of those components. In one embodiment this is achieved by convolving the intensity profile with a quadrature filter to derive the phase and amplitude of a pair of odd and even components of the profile in the spatial frequency domain. The phase and amplitude of these components is characteristic of different shapes in the intensity profile. The difference between the odd and even components, which is a measure of the “feature asymmetry” is, for example, a maximum for a step edge. Thus by setting constraints on the value of the feature asymmetry it is possible to determine that the area of the image under consideration corresponds to the shape being sought. The values of feature asymmetry and local amplitude (which is based on the amplitude of the two components), are included in the label.
Preferably the filters are quadrature wavelet filters, e.g. log-Gabor filters, so that the intensity profile is convolved with odd and even wavelets. The scale of the wavelet is chosen in accordance with the scale of the features to be detected, and to be much larger than the scale of noise in the image. This means that the technique selects features according to their shape and scale, but regardless of the value of intensity.
The filters may be oriented in different directions across the image to detect image features having different orientations. The label may then include a measure of the feature orientation, which can be derived from the relative responses of the differently oriented filters.
The image processing technique of the invention may be used as a precursor to tracking detected image features through a sequence of image frames. The provision of the labels carrying information about the detected features is particularly useful in such a tracking process. For instance, rather than simply searching for the closest image feature in two successive frames, it is possible also to compare the labels of the detected image features in the two frames and to define them as relating to the same image feature if the labels satisfy predefined search criteria.
Such search criteria may include a condition on the value of the feature asymmetry of the two features being detected and a condition on the orientation of the detected features (for instance that they are oriented similarly).
Where the label includes a measure of the velocity of the feature, the search area from frame-to-frame may be defined in accordance with the velocity, and the search criteria may include a condition on the velocity.
The invention is particularly applicable to ultrasound or magnetic resonance images, but also to x-ray and other imaging modalities. The embodiment described below relates to echocardiography, but the invention is applicable to ultrasound images in general, such as of different organs and tissues e.g. coronary arteries, liver, foetus etc, and to different ultrasound modalities such as the use of contrast and different signal processing techniques such as Doppler imaging and harmonic imaging. For instance in echocardiography, by setting the shape model appropriately the invention is adaptable to the detection of any features corresponding to a step change in intensity, such as the ventricular walls.
The invention may be embodied in a system adapted to perform the image processing method, and it may be embodied by a computer program comprising program code means for executing the method. Thus the invention further provides for a computer program storage medium carrying such a computer program, and also a computer system programmed to carry out the method.